| Authors |
|
| Publication date |
2015
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| Host editors |
-
B. De Ruyter
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A. Kameas
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P. Chatzimisios
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I. Mavrommati
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| Book title |
Ambient Intelligence
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| Book subtitle |
12th European Conference, AmI 2015, Athens, Greece, November 11-13, 2015 : proceedings
|
| ISBN |
|
| ISBN (electronic) |
|
| Series |
Lecture Notes in Computer Science
|
| Event |
Ambient Intelligence : 12th European Conference
|
| Pages (from-to) |
219-235
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| Publisher |
Cham: Springer
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| Organisations |
-
Faculty of Science (FNWI) - Informatics Institute (IVI)
|
| Abstract |
We present a method for measuring gait velocity using data from an existing ambient sensor network. Gait velocity is an important predictor of fall risk and functional health. In contrast to other approaches that use specific sensors or sensor configurations our method imposes no constraints on the elderly. We studied different probabilistic models for the description of the sensor patterns. Experiments are carried out on 15 months of data and include repeated assessments from an occupational therapist. We showed that the measured gait velocities correlate with these assessments.
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| Document type |
Conference contribution
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| Language |
English
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| Published at |
https://doi.org/10.1007/978-3-319-26005-1_15
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